ML algorithms can analyze vast amounts of experimental and theoretical data to identify promising catalyst candidates. For example, ML models can predict the activity, stability, and selectivity of catalysts based on their chemical composition and structure. This predictive capability allows researchers to focus their efforts on the most promising candidates, thereby accelerating the discovery process.
